Performance Analysis of Data Mining Algorithms to Generate Frequent Itemset

International Journal of Artificial Intelligence and Knowledge Discovery

Dharmender Kumar¹ 

关键词: Data Mining;    Apriori;    Frequent Itemset Mining;   

DOI  :  

学科分类：建筑学

来源: RG Education Society

【 摘 要 】

Gigantic amount of data records i.e. in terabytes or more are available in science, industry, business and many other areas. Such data can provide rich information of strategic importance which can be utilized. But the problem is how to obtain this information. Today the answer is data mining! Now a day the frequent itemset mining has became one of the hottest research topics in the field of data mining. The past decades has witnessed that hundereds of research papers have been published for presenting new or improvements in the existing frequent itemset mining algorithms.  In this paper the frequent itmset mining algoritms i.e. Apriori, FP-Growth, ECLAT, and RELIM are presented with their theoretical and experimental analysis

【 授权许可】

Unknown